Miquel Nieto is a Research Fellow in Machine Learning at the University of Bristol with over a decade of experience applying AI to healthcare and sensor data. He holds a PhD in Computer Science and two MSc degrees—one in Machine Learning and Data Mining from Aalto University and another in Artificial Intelligence from Catalan universities—bringing strong theoretical grounding to practical health-focused projects. His work centers on interpretable classifiers that provide calibrated confidence estimates, bridging methodological advances and real clinical needs through the LEAP Digital Health Hub and SPHERE initiatives. Miquel’s background spans deep learning, distributed systems, and embedded electronics, reflecting earlier engineering roles that inform his pragmatic research approach. He has a track record of interdisciplinary collaboration across European research networks (including the TAILOR Network) and maintains an active professional presence via his personal website.
11 years of coding experience
13 years of employment as a software developer
Master's programme in Machine Learning and Data Mining Computer Science, Master's programme in Machine Learning and Data Mining Computer Science at Aalto University
Ingeniería técnica en Informática de sistemas Computer Engineering, Ingeniería técnica en Informática de sistemas Computer Engineering at Facultat d'Informàtica de Barcelona
UPC Universitat Politècnica de Catalunya
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at University of Bristol
Contributions:1 release, 104 commits, 5 PRs in 3 years 2 months
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Miquel Nieto - Research Fellow at University of Bristol